Abstract

The search for protein molecular surfaces similarity is completely independent of sequence and secondary structure and has a power to reveal further functional relationships between proteins. In order to make the comparison more efficient, we proposed a method that combines advantages from both graph based clique detection and vectors spatial arrangement clustering. The graph will be created based on the vector spatial arrangement clustering, in which only pair of two vectors with the same clustered index are compared for the high-speed computational process. From the graph created, the largest clique is correspond to a the most similar part between the two molecular surfaces. The geometrical similarity of two molecular surfaces generally requires prior identification of the transformation to achieve an optimal superposition between selected vertices of the two molecular surfaces. Based on a recent method for the protein function identification by the molecular surface comparison between the active sites and the unknown protein. Following the idea that the function of protein depends on its molecular surface, we applied our method on the surface dataset and calculated the similarity score. Early result indicate that this method was performed quick enough in a normal workstation.